In this week's special episode we look at the Salesforce Dreamforce 2023 conference, provide an overview of the major announcements and talk with three guests about Salesforce's AI offerings. I'm joined by Rob Katz, VP of Product - Responsible AI and Tech; Avanthika Ramesh, Director, Product - Salesforce AI; and Bobby Brill, Sr Director, Product - Salesforce Einstein Discovery.

Live Blog from Dreamforce 2023 keynote.

Businesses have the opportunity to enhance customer service (CS) by incorporating generative AI in their customer service systems. Powerful large language models (LLMs) can enable businesses to provide next-level customer experiences (CX) while improving CS agent performance and job satisfaction. Let’s look at the transformative potential of generative AI for enhancing CX.

In this episode I chat with Tim Handorf, EVP and GM of G2 Labs about the use of generative AI for intelligent chatbots. His team launched several chatbots this year on the G2 website to assist both software buyers and software sellers on the marketplace. The bots have provided a significant enhancement to the customer experience while using the G2 platform.

Unless you live under a rock, you’re hearing about generative AI and its capabilities to generate text, images, audio, and video content everywhere you turn. As a business leader, it is crucial to understand the current and potential impact of generative AI and how to leverage its power. This guide provides a business-focused overview of generative AI and offers insights into how it can be integrated into your organization's strategy.

Generative AI tools like OpenAI’s ChatGPT and Anthropic’s Claude are becoming increasingly popular for businesses, but getting the output you want is not intuitive and often misses the mark. Large Language Models (LLM) can assist in a variety of tasks, including writing emails, creating social media campaigns, summarizing reports, and even accelerating customer service interactions. The quality of the prompt directly influences the accuracy and relevance of the AI-generated output. Knowing how to get the most out of them is a skill that is increasingly in demand. Crafting effective prompts is the key to unlocking the full potential of these GenAI tools.

Generative AI is a rapidly evolving technology with the potential to significantly enhance project management. By automating tasks, identifying risks, and generating insights, generative AI can help project managers (PMs) save time, improve efficiency, and deliver better results.

Here are some of the ways generative AI is being used in project management today:

Automating tasks: Generative AI can be used to automate repetitive tasks, such as identifying resources, scheduling tasks, tracking progress, and generating reports. This frees up PMs to focus on more strategic and value-added activities.

Identifying risks: Generative AI can be used to identify potential risks and issues early on in the project lifecycle. This helps PMs take steps to mitigate these risks and avoid costly delays or failures.

Generating insights: Generative AI can be used to generate insights from data, such as identifying trends, patterns, and relationships. This helps PMs make better decisions and improve the overall project outcomes.

Transcript: In this episode I chat with Nathaniel Mahowald and Mike Gioia from Pickaxe, a no-code AI platform. We covered a wide variety of topics including the use cases of no-code AI platforms, some real examples from their customers, prompt tips and tricks and a few other topics. You can check out their platform and Pickaxe Builder

Human-machine collaboration refers to the synergistic partnership between humans and machines, leveraging the strengths of both to achieve better results than either could alone. The idea behind this collaboration is to combine human intuition, creativity, and flexibility with machine precision, speed, and the ability to handle vast amounts of data. <image created by Boodle.ai ImageBot>

At the recent SIGNAL 2023 event, Twilio gave a glimpse into its view of the future of AI-powered customer engagement with the introduction of an assortment of new AI capabilities under the CustomerAI banner. The combination of the power of large language models (LLMs) with real-time customer data from Twilio’s customer data platform (CDP) Segment can offer companies a set of tools designed to improve and enhance customer interactions. <image created by Boodle.ai ImageBot>

Transcript: In our show today I’m joined by Soribel Feliz, a thought leader in the fields of Responsible AI and emerging tech, and we look at balancing the use of new AI enabled solutions, particularly generative AI, with privacy and regulatory compliance challenges.

In recent years, the productivity of sales teams has experienced a noticeable decline, posing challenges for businesses attempting to hit their financial targets. Automation and generative AI, which have advanced a great deal over the past year or so, do offer some potential for helping turn this trend around. These technological advancements could potentially revolutionize sales team performance and rejuvenate their productivity. By streamlining repetitive tasks, providing valuable insights, and enabling personalized interactions, automation and generative AI have the power to enhance sales team performance. <image created by Boodle.ai ImageBot>

"Flipping the classroom" is an educational approach where students first encounter new material outside of class, typically through video lectures or reading assignments, and then use class time to work on problem-solving, discussions, or other active learning strategies. Generative AI can play a significant role in facilitating and enhancing this approach in various ways:

Transcript for Disambiguation Podcast Episode 2 with Guest Jakub Stefaniak

AI technology has revolutionized the way we approach data analysis and modeling. For these applications to be successful, though, the data must be properly prepped. Data preparation is the process of organizing data into a format that can be used to create effective AI models. Without proper data preparation, AI models will not be able to effectively analyze and interpret data. As technology advances, artificial intelligence (AI) models and algorithms are becoming increasingly important for businesses and organizations around the world. However, the success of these AI models and algorithms is dependent on how well the data is prepared. Data preparation is essential for ensuring that AI models and algorithms are accurate, reliable, and effective.

Disambiguation, a podcast that aims to "remove the confusion around" artificial intelligence (AI), generative AI and business automation by looking at the business solutions available today to improve business outcomes and gain competitive advantage. Check it out on YouTube or any of the major podcast platforms.

Generative AI has revolutionized the way we think about Artificial Intelligence (AI) and its applications. By incorporating generative AI into a cloud-based platform, you can unlock an unprecedented level of efficiency and innovation for your applications. With generative AI, you can leverage advanced AI technologies to create intelligent solutions tailored to your specific needs. In this post we’ll explore how generative AI can enhance the services of a cloud-based platform and increase the effectiveness of applications built on the cloud platform.

We are excited to announce the official launch of the Disambiguation podcast.

"Disambiguation is the process of removing confusion around terms that express more than one meaning and can lead to different interpretations of the same string of text."

Host Michael Fauscette of Arion Research; a leading technology analyst, tech startup advisor, consultant, board member, and storyteller; and his guests "remove the confusion around" artificial intelligence (AI), generative AI and business automation by looking at the business solutions available today to improve business outcomes and gain competitive advantage.

Infographic from the AI Adoption survey, August 2023.

Since last fall there has been a rapidly growing obsession with generative AI and particularly OpenAI’s ChatGPT. There are a number of open and closed large language models (LLM) from a variety of startups gaining users at a whirlwind pace, as well as several cloud providers offering open integrations and LLMs of their own. The buzz on generative AI started mostly positive but as with most technology there quickly emerges a darker side as well. For generative AI this ranges from the capability to generate overwhelming misinformation campaigns to security and privacy challenges.